Unruptured intracranial aneurysms Prediction of growth and rupture

This thesis advances the understanding of unruptured intracranial aneurysms (UIAs), focusing particularly on risk prediction, aneurysm growth, and aneurysm wall enhancement (AWE). Despite the relatively low annual rupture rate of UIAs, their unpredictable behaviour and devastating consequences necessitate precise risk stratification and individualized management strategies. A major component of this work measured the absolute risk of rupture after aneurysm growth. In a multicentre cohort of 312 patients with growing aneurysms, the 1-year rupture risk was 4.3%. Based on this dataset, the triple-S model, integrating three independent predictors, aneurysm size, site, and shape, was developed to estimate the rupture risk following growth, ranging from 2.1% to 10.6% within the first year. This model provides clinicians with a practical tool to guide decisions about preventive treatment. This thesis investigated AWE using gadoliniumenhanced magnetic resonance aneurysm wall imaging (MR-AWI). Although AWE had been linked to aneurysm instability in cross-sectional studies, its longitudinal predictive value remained uncertain. In this work, AWE predicted aneurysm growth or rupture during short-term follow-up, but this association diminished after adjustment for aneurysm size, except in aneurysms smaller than 7 mm, where AWE may retain predictive potential. Extending the observation period to 7.5 years, aneurysms with AWE demonstrated a significantly higher probability of long-term instability than those without enhancement, independent of aneurysm size and patient age. These findings support AWE as a marker of chronic wall pathology and highlight the value of incorporating wall imaging sequences into conventional MRA protocols for individualized risk assessment. Longitudinal imaging of 387 aneurysms showed that AWE was stable over time, with enhancement appearing or disappearing in only 5.2% of aneurysms during a median follow-up of 12 months. This stability suggests that the underlying inflammatory and hemodynamic processes are long-lasting rather than transient. A complementary 3D morphometric study revealed that AWE at baseline was associated with increasing aneurysm wall curvedness over long-term follow-up (median 5.8 years). The proportion of aneurysms with increased curvedness was substantially higher among those with AWE (30%) compared with those without (4%), independent of size (OR 6.1, 95%CI 1.01–50.3). These results indicate that AWE marks biological mechanisms that promote structural remodelling and shape irregularity, morphological features known to precede rupture. In conclusion, this thesis highlights the value of combining clinical, morphological, and imaging-based risk assessment to improve decision-making in patients with UIAs. The demonstrated stability and prognostic significance of AWE, alongside refined models such as triple-S, lay the groundwork for more precise and patientcentred care. Keypoints ● Risk stratification of UIAs remains challenging due to the limitations of existing rupture risk models, particularly for small aneurysms. ● This thesis introduces the triple-S model for individualized absolute rupture risks after aneurysm growht. Also, it demonstrates that AWE is a stable imaging marker that independently predicts aneurysm instability. ● The triple-S model can support clinical decision-making and treatment prioritization after aneurysm growth, whereas AWE shows promise as a marker of chronic wall pathology and should be incorporated into future prospective cohorts to refine individualized risk prediction in the general UIA population.